Source code for util

'''
Collection of utility functions with no other obvious home.
'''
from itertools import izip, cycle
from collections import defaultdict
import json
import os
import math
import gzip


def diff_count(data1, data2):
    '''
    Count the number of differences is two sets of data
    '''
    return sum(x != y for x, y in izip(data1, data2))


def open_file_method(filename):
    '''
    This chooses the proper way to open a file by examining its extension.
    Returns the function to use, either "open" or "gzip"
    '''
    extension = filename.split('.')[-1]
    if extension == 'gz':
        return gzip.open
    return open


def load_configurations(filenames):
    '''
    Given a list of files containing json encoded dictionaries, combined
    the data into a single dictionary.  Will attempt to use file extension
    to detect correct file type.

    Parameters:

    - ``filenames``: The list of files paths.
    '''
    result = {}
    for filename in filenames:
        file_method = open_file_method(filename)
        with file_method(filename, 'r') as f:
            result.update(json.load(f))
    return result


def save_configuration(filename, data):
    '''
    Write a dictionary to the specified file in json format.  Will attempt to
    use file extension to detect correct file type.

    Parameters

    - ``filename``: The path to write to.
    - ``data``: The data to be written.
    '''
    file_method = open_file_method(filename)
    with file_method(filename, 'w') as f:
        json.dump(data, f)


def save_list(filename, data):
    '''
    Write a list of dictionaries to the file in a more human readable way.
    Will attempt to use file extension to detect correct file type.

    Parameters

    - ``filename``: The path to write to.
    - ``data``: The list of dictionaries to be written.
    '''
    file_method = open_file_method(filename)
    with file_method(filename, 'w') as f:
        f.write('[' + os.linesep)
        for lineNumber, line in enumerate(data):
            json.dump(line, f)
            if lineNumber != len(data) - 1:
                f.write(",")
            f.write(os.linesep)
        f.write(']' + os.linesep)


def meanstd(data):
    '''
    Returns the mean and standard deviation of the given data.

    Parameters:

    - ``data``: The data to find the mean and standard deviation of.
    '''
    try:
        mean = float(sum(data)) / len(data)
        std = math.sqrt(sum([(value - mean) ** 2 for value in data])
                        / len(data))
        return mean, std
    except (ZeroDivisionError, TypeError):
        return 0, 0


def find_median(data):
    '''
    Returns the median of the data.
    '''
    ordered = sorted(data)

    length = len(data)
    middle = length // 2
    if length % 2 == 1:
        return ordered[middle]
    else:
        return (ordered[middle] + ordered[middle - 1]) / 2.0


def median_deviation(data, median=None):
    '''
    Returns the median and the median absolute deviation of the data.

    Parameters:

    - ``data``: The data to find the medians of.
    - ``median``: If the median is already known you can pass it in to save
      time.
    '''
    if median is None:
        median = find_median(data)
    return  median, find_median([abs(x - median) for x in data])


def bitcount(integer):
    '''
    Counts the number of set bits in an integer
    '''
    return bin(integer).count('1')


def set_fonts():
    '''
    Configures matplotlib to use only Type 1 fonts, and sets the figure size
    such that those fonts will be legible when the figure is inserted in
    a publication.
    '''
    import matplotlib
    matplotlib.rcParams['ps.useafm'] = True
    matplotlib.rcParams['pdf.use14corefonts'] = True
    matplotlib.pyplot.figure(figsize=(5, 5))

# Generator used when plotting to cylce through the different line styles
linecycler = cycle(["-", "--", "-.", ":"])

# Dictionary converter from original name to name used in paper
pretty_name = {"normal": "Normal",
               "reorder": "Reorder",
               "dag": "DAG",
               "single": "Single",
               "skip": "Skip",
               "accumulate": "Accumulate"}

# Specifies what order lines should appear in graphs
line_order = {'normal': 1,
              'reorder': 2,
              'dag': 3,
              }